Back-of-the-envelope machine learning (specifically neural networks) calculations
I have one to share. This is no formula, but a general thing I have noticed. 

The number of neurons + neurons should be proportionate, in some way, to the complexity of the classification.

Although this is fairly basic and widely known, it has helped me in many times to consider one thing: how many at a minimum does it need?